Infection testing at scale: An examination of pooled testing diagnostics
By: Jain, Tarun and Jain, Bijendra Nath
.
Material type: 
BookPublisher: Vikalpa: The Journal for Decision Makers Description: 46(1), Jan-Mar, 2021: p.13-26.Subject(s): Diagnostics, Pooled testing, COVID-19, Coronavirus
In:
Vikalpa: The Journal for Decision MakersSummary: In pandemics or epidemics, public health authorities need to rapidly test a large number of individuals without adequate testing kits. We propose a testing protocol to accelerate infection diagnostics by combining multiple samples, and in case of positive results, re-test individual samples. The key insight is that a negative result in the first stage implies negative infection for all individuals. Thus, a single test could rule out infection in multiple individuals. Using simulations, we show that this protocol reduces the required number of testing kits, especially when the infection rate is low, alleviating a key bottleneck for public health authorities in times of pandemics and epidemics such as COVID-19. Our proposed protocol is expected to be more effective when the infection rate is low, which suggests that it is better suited for early stage and large-scale, population-wide testing. However, the managerial trade-off is that the protocol has costs in additional time for returning test results and an increased number of false negatives. We discuss applications of pooled testing in understanding population-wide testing to understand infection prevalence, to diagnose infections in high-risk groups of individuals, and to identify disease cold spots. – Reproduced
| Item type | Current location | Call number | Vol info | Status | Date due | Barcode |
|---|---|---|---|---|---|---|
Articles
|
Indian Institute of Public Administration | 46(1), Jan-Mar, 2021: p.13-26 | Available | AR125758 |
In pandemics or epidemics, public health authorities need to rapidly test a large number of individuals without adequate testing kits. We propose a testing protocol to accelerate infection diagnostics by combining multiple samples, and in case of positive results, re-test individual samples. The key insight is that a negative result in the first stage implies negative infection for all individuals. Thus, a single test could rule out infection in multiple individuals. Using simulations, we show that this protocol reduces the required number of testing kits, especially when the infection rate is low, alleviating a key bottleneck for public health authorities in times of pandemics and epidemics such as COVID-19. Our proposed protocol is expected to be more effective when the infection rate is low, which suggests that it is better suited for early stage and large-scale, population-wide testing. However, the managerial trade-off is that the protocol has costs in additional time for returning test results and an increased number of false negatives. We discuss applications of pooled testing in understanding population-wide testing to understand infection prevalence, to diagnose infections in high-risk groups of individuals, and to identify disease cold spots. – Reproduced
There are no comments for this item.